The broad objective of the Resource is to apply advanced methods in computer science, particularly in Artificial Intelligence (AI), to biomedical problems. The Resource will promote the development and use of computer systems for intelligent consultation in medical diagnosis and therapy and for research assistance in processes of scientific experimentation and theory formation. The organization of knowledge in a domain, both formal and judgmental (obtained from experts), and its representation in computers, is of central importance in the Resource. Knowledge-based systems that rely on models, heuristic rules and other representations that facilitate the use of knowledge in various reasoning tasks, are being developed and studied. The Resource continues to have three major areas of study: Area 1 - Medical Modeling and Decision Making in several medical domains with emphasis on collaborative development of consultation systems in rheumatology and ophthalmology; Area 2 - Modeling of Belief Systems and Commonsense Reasoning with emphasis on the psychology of plan recognition and handling of stereotypes; and Area 3 - Artificial Intelligence studies with emphasis on Representations, Interpretation processes, and problems of knowledge and expertise acquisition. The Resource will continue to sponsor national Artificial Intelligence in Medicine (AIM) Workshops for the AIM community; and it will continue its other efforts in AIM dissemination and training. After its enhancement, the RUTGERS/LCSR facility is now serving as a shared computer resource, in coordination with the SUMEX-AIM facility, for the national AIM community. Our research is interdisciplinary and interinstitutional. The studies in Medical Modeling and Decision Making are performed jointly by computer and medical scientists at Rutgers and elsewhere in the country and abroad. Work on a rheumatology consultant is developing in close collaboration with investigators at the University of Missouri and other institutes. Work in glaucoma and neurophysiol is continuing in collaboration with ONET investigators at Washington University and other places.